US7860197B2 - Spectrum-sensing algorithms and methods - Google Patents

Spectrum-sensing algorithms and methods Download PDF

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US7860197B2
US7860197B2 US11/856,472 US85647207A US7860197B2 US 7860197 B2 US7860197 B2 US 7860197B2 US 85647207 A US85647207 A US 85647207A US 7860197 B2 US7860197 B2 US 7860197B2
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channel
candidate
channels
spectrum
vacant
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US20080080604A1 (en
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Youngsik Hur
Chang-Ho Lee
Jeongsuk Lee
Kihong Kim
Haksun Kim
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Samsung Electro Mechanics Co Ltd
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Samsung Electro Mechanics Co Ltd
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Priority to US11/856,472 priority Critical patent/US7860197B2/en
Priority to FI20075665A priority patent/FI20075665L/fi
Priority to DE102007046595A priority patent/DE102007046595A1/de
Priority to KR1020070098325A priority patent/KR100978652B1/ko
Priority to FR0757953A priority patent/FR2906657B1/fr
Priority to CN2007101514248A priority patent/CN101155423B/zh
Priority to GB0719063A priority patent/GB2442571B/en
Assigned to SAMSUNG ELECTRO MECHANICS reassignment SAMSUNG ELECTRO MECHANICS ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: HUR, YOUNGSIK, LEE, CHANGO-HO, KIM, HAKSUN, KIM, KIHONG, LEE, JEONGSUK
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69—Spread spectrum techniques
    • H04B1/707—Spread spectrum techniques using direct sequence modulation
    • H04B1/7073—Synchronisation aspects
    • H04B1/7085—Synchronisation aspects using a code tracking loop, e.g. a delay-locked loop
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/0004—Modulated-carrier systems using wavelets
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • H04B17/327—Received signal code power [RSCP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04K—SECRET COMMUNICATION; JAMMING OF COMMUNICATION
    • H04K3/00—Jamming of communication; Counter-measures
    • H04K3/20—Countermeasures against jamming
    • H04K3/22—Countermeasures against jamming including jamming detection and monitoring
    • H04K3/224—Countermeasures against jamming including jamming detection and monitoring with countermeasures at transmission and/or reception of the jammed signal, e.g. stopping operation of transmitter or receiver, nulling or enhancing transmitted power in direction of or at frequency of jammer
    • H04K3/226—Selection of non-jammed channel for communication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/14—Spectrum sharing arrangements between different networks

Definitions

  • the invention relates to cognitive radio applications, and more particularly to spectrum sensing algorithms and other decision methods.
  • the FCC Federal Communications Commission
  • the FCC Federal Communications Commission
  • the FCC Federal Communications Commission
  • licenses a number of spectrum segments to entities and individuals for commercial or public use. These licenses may allow these entities and individuals (“licensees”) an exclusive right to utilize their respective licensed spectrum segments for a particular geographical area for a certain amount of time. Such licensed spectrum segments are believed to be necessary in order to prevent or mitigate interference from other sources.
  • the available spectrum if particular spectrum segments are not in use at a particular location at a particular time (“the available spectrum”), another device should be able to utilize such available spectrum for communications. Such utilization of the available spectrum would make for a much more efficient use of the radio spectrum or portions thereof.
  • CRs Cognitive Radios
  • CRs are seen as a solution to the current low usage or under utilization of the radio spectrum. It is a technology that will enable flexible, efficient and reliable spectrum use by adapting the radio's operating characteristics to the real-time conditions of the environment. CRs have the potential to utilize the large amount of unused spectrum in an intelligent way while not interfering with other incumbent devices in frequency bands already licensed for specific uses. CRs are enabled by the rapid and significant advancements in radio technologies (e.g., software-defined radios, frequency agility, power control, etc.), and can be characterized by the utilization of disruptive techniques such as wide-band spectrum sensing, real-time spectrum allocation and acquisition, and real-time measurement dissemination.
  • disruptive techniques such as wide-band spectrum sensing, real-time spectrum allocation and acquisition, and real-time measurement dissemination.
  • Constraints of such spectrum sensing algorithms and methods may include the primary spectrum users not providing any spectrum usage information for the CR users.
  • Additional constraints may include the primary spectrum user signals coming from transmitters located at the proximities of CR receivers or at very distant places.
  • spectrum-sensing algorithms and methods may need to detect the primary signals with extremely low power-level even below the sensitivity requirement of the link between the incumbent spectrum users.
  • these primary spectrum user signals or CR user signal may have the signal power enough to go beyond the CR receiver's dynamic range.
  • This wide dynamic range of received signals may be a very challenging issue to guarantee the detection sensitivity as well as the detection reliability.
  • a threshold value is applied to this wide range of signal level case, it may cause mis-detection events for the sake of false alarm rate. Otherwise, it may increase false alarm rate to provide better detection sensitivity. Therefore, the threshold selection may be an important factor for the uniform performance of the spectrum sensing algorithms and methods.
  • a further constraint is that the time consumed to detect or sense the spectrum over wideband frequency span should be minimized. In other words, the sensing time should be minimized to improve the overall spectral efficiency through the spectrum sensing algorithms and methods. Accordingly, there is a need in the industry for spectrum sensing algorithms and methods in the CR system to locate unoccupied spectrum segments in an efficient and accurate manner.
  • the cognitive radio may include one or more spectrum sensing algorithms or methods in conjunction with frequency-agile operation.
  • the spectrum sensing algorithms or methods may utilize wavelet transforms to provide a multi-resolution sensing feature.
  • Spectrum sensing algorithms or methods in accordance with an embodiment of the invention may include a tri-stage procedure: (i) a coarse-scanning stage, (ii) a fine-scanning stage, and (iii) a final decision stage.
  • Other embodiments of the invention may include alternative or fewer combinations of the tri-stage procedure.
  • double testing methods i.e., channel power testing and peak-count testing
  • dual-mode thresholds e.g., strong-mode and weak-mode thresholds
  • mode specific averaging options may be available in accordance with other embodiments of the invention to minimize the overall sensing time.
  • the method may include receiving an input spectrum having a plurality of channels, performing a coarse scan of the plurality of channels of the input spectrum to determine one or more occupied candidate channels and vacant candidate channels, where the coarse scan is associated with a first resolution bandwidth and a first frequency sweep increment, performing a fine scan of the occupied candidate channels and the vacant candidate channels to determine actually occupied channels and actually vacant channels, where the fine scan is associated with a second resolution bandwidth and a second frequency sweep increment, and storing an indication of the actually occupied channels and the actually vacant channels.
  • the method may include providing an input radio frequency (RF) spectrum having a plurality of channels, and analyzing the plurality of channels of the input RF spectrum using a coarse-scanning stage to determine one or more strong candidate channels, weak candidate channels, and vacant candidate channels, where the coarse-scanning stage is associated with a first resolution bandwidth and a first frequency sweep increment.
  • the method may also include analyzing the one or more strong candidate channels, weak candidate channels, and vacant candidate channels using a fine-scanning stage to determine actually occupied channels and actually vacant channels, where the fine-scanning stage is associated with a second resolution bandwidth and a second frequency sweep increment, and storing an indication of the actually occupied channels and the actually vacant channels.
  • RF radio frequency
  • the system may include an input radio frequency (RE) spectrum having a plurality of channels, first means for determining one or more strong candidate channels, weak candidate channels, and vacant candidate channels from the input RF spectrum, where the first means is associated with a first resolution bandwidth and a first frequency sweep increment, and second means for determining actually occupied channels and actually vacant channels based upon the one or more strong candidate channels, weak candidate channels, and vacant candidate channels, where the second means is associated with a second resolution bandwidth and a second frequency sweep increment.
  • RE radio frequency
  • FIG. 1A illustrates example wavelet waveforms w 1 (t) and w 2 (t) having different pulse widths, according to an example embodiment of the invention.
  • FIG. 1B illustrates the corresponding spectrums of FIG. 1A , according to an example embodiment of the invention.
  • FIG. 2 illustrates a block diagram of an MRSS front-end implementation in accordance with an example embodiment of the invention.
  • FIG. 3A illustrates an example input RF signal spectrum, according to an example embodiment of the invention.
  • FIG. 3B illustrates spectrum detection in a sparse manner, according to an example embodiment of the invention.
  • FIG. 3C illustrates spectrum detection in a precise manner, according to an example embodiment of the invention.
  • FIG. 4 illustrates an example flow diagram of a spectrum-sensing and decision procedure, according to an example embodiment of the invention.
  • FIG. 5 illustrates a flow diagram of the coarse scanning procedure, according to an example embodiment of the invention.
  • FIG. 6 illustrates an example result of a coarse MRSS, according to an example embodiment of the invention.
  • FIG. 7 shows an example flow diagram of a fine scanning procedure and a final decision procedure, according to an example embodiment of the invention.
  • FIGS. 8A-8D illustrate a more detailed flow chart of a fine scanning procedure and the final decision procedure, according to an example embodiment of the invention.
  • FIG. 9 illustrates an example result of the fine MRSS, according to an embodiment of the invention.
  • Embodiments of the invention may provide spectrum sensing algorithms and methods utilized in cognitive radios for exploiting limited spectrum resources.
  • the cognitive radios may allow for negotiated and/or opportunistic spectrum sharing over a wide frequency range covering a plurality of mobile communication protocols and standards.
  • the cognitive radio may be able to intelligently detect the usage of a segment in the radio spectrum and to utilize any temporarily unused spectrum segment rapidly without interfering with the communication between other authorized users.
  • the use of these cognitive radios may allow for a variety of heterogeneous wireless networks to coexist with each other. These wireless networks may include cellular networks, wireless personal area networks (PAN), wireless local area networks (LAN), and wireless metro area networks (MAN). These wireless networks may also coexist with television networks. Other types of networks may also be available in accordance with other embodiments of the invention.
  • PAN personal area networks
  • LAN wireless local area networks
  • MAN wireless metro area networks
  • a spectrum-sensing module of a cognitive radio may utilize wavelet transforms in providing a multi-resolution spectrum sensing feature, which may be referred to as Multi-Resolution Spectrum Scanning (MRSS).
  • MRSS Multi-Resolution Spectrum Scanning
  • the use of MRSS for the spectrum-sensing module of a cognitive radio may allow for a flexible detection resolution without necessarily requiring an increase in the hardware burden.
  • a wavelet transform may be applied to a given time-variant signal to determine a correlation between the given time-variant signal and a basis function (e.g., a wavelet pulse) for the wavelet transform.
  • This correlation may be known as the wavelet transform coefficient, which may be initially determined in analog form, according to an embodiment of the invention.
  • the wavelet pulse that serves as the basis function for the wavelet transform utilized with MRSS may be varied according to an embodiment of the invention.
  • the wavelet pulses for the wavelet transform may be varied in bandwidth, carrier frequency, and/or time period.
  • the spectral contents provided through the wavelet transform coefficient for the given time-variant signal may be represented with a scalable resolution or multi-resolution. Indeed, by changing the wavelet pulse width and carrier frequency of the wavelet pulses after maintaining them within a certain interval, the wavelet transform may provide an analysis of the spectral contents of the time-variant signals in accordance with an embodiment of the invention.
  • a wavelet transform including a Fourier transform
  • a basis function may be used to derive a spectral representation of the signal provided in the time domain.
  • the correlation e.g., a wavelet transform coefficient
  • a basis function perhaps a sinusoidal basis function
  • the wavelet pulse utilized as the basis function of the wavelet transform may be varied according to an example embodiment of the invention.
  • certain types of basis functions for wavelet pulses may have resolution bandwidth as an additional freedom-of-design, according to an example embodiment of the invention.
  • the spectral contents provided by the wavelet transform correlation may be represented with scalable resolution or multi-resolution.
  • FIG. 1A illustrates two examples of wavelet-waveforms w 1 (t) and w 2 (t) having different pulse widths, according to an example embodiment of the invention.
  • FIG. 1B illustrates the corresponding spectrums of FIG. 1A that have different resolution bandwidths, according to an example embodiment of the invention.
  • FIG. 2 illustrates a block diagram for an exemplary MRSS front-end 200 in accordance with an embodiment of the invention.
  • the MRSS front-end 200 may include an analog wavelet waveform generator 204 , analog multipliers 206 a , 206 b , analog integrators 208 a , 208 b , and a timing clock 209 .
  • the timing clock 209 may provide timing signals utilized by the wavelet generator 204 , the analog integrators 208 a , 208 b , and/or the sample and hold (S/H) circuits 228 a , 228 b.
  • the wavelet generator 204 may generate a chain of wavelet pulses w(t) 218 that are modulated with I- and Q-sinusoidal carriers cos(2 ⁇ f k t) 220 a and sin(2 ⁇ f k t) 220 b with a given local oscillator 214 (LO) frequency to form a chain of modulated wavelet pulses w I,k (t) 222 a , w Q,k (t) 222 b .
  • the I-component signal 220 a may be equal in magnitude but 90 degrees out of phase with the Q-component signal 220 b .
  • the chain of modulated wavelet pulses w I,k (t) 222 a , w Q,k (t) 222 b may then be multiplied by the time-variant input signal r(t) 216 by respective analog multipliers 206 a , 206 b to form analog input signals y I,k (t) 224 a and y Q,k (t) 224 b into the respective analog integrators 208 a , 208 b .
  • the analog integrator 208 provides the output of the wavelet transform analog correlation values z I,k (t) 226 a and z Q,k (t) 226 b.
  • these analog correlation values z I,k (t) 226 a and z Q,k (t) 226 b may be calculated using wavelet pulses w(t) 218 having a given spectral width—that is, the spectrum sensing resolution.
  • the local oscillator 214 frequency of the I- and Q-sinusoidal carriers 220 a , 220 b may then be swept with a particular increment. Accordingly, the signal power magnitudes and the frequency values within the time-variant input signal r(t) 216 may be detected in the analog correlation values z I,k (t) 226 a and z Q,k (t) 226 b over the spectrum range of interest.
  • an MRSS front end 200 in accordance with an embodiment of the invention may examine a very wide spectrum span in a fast and sparse manner.
  • very precise spectrum searching may be realized with a wide wavelet pulse w(t) 218 and the delicate or small adjustment of the LO 214 frequency.
  • multi-resolution may be achieved without any additional digital hardware burdens.
  • the analog correlation values 226 a (Z I,k (t)), 226 b (Z Q,k (t)) determined at the outputs of analog integrators 208 a , 20 b may be provided to analog-to-digital converters (ADCs) 210 a , 210 b .
  • sample-and-hold (S/H) circuits 228 a , 228 may be provided to hold voltages of analog correlation values Z I,k (t) 226 a and Z Q,k (t) 226 b to allow the ADCs 210 a , 210 b to properly digitize the analog correlation values z I,k (t) 226 a and z Q,k (t) 226 b .
  • the digitized correlation values 230 a , 230 b may be provided to post-signal processing module 212 for processing and decision of the spectrum usage status.
  • FIGS. 3A-3C illustrates a scalable resolution control in the frequency domain with the use of wavelet pulses.
  • FIG. 3A illustrates an example input RF signal spectrum, according to an example embodiment of the invention.
  • FIG. 3B illustrates an example spectrum detection in a sparse or coarse manner, according to an example embodiment of the invention. More specifically, in FIG. 3B , the MRSS simulation result illustrates a wideband spectrum shape with blunt peaks for three input signals.
  • FIG. 3C illustrates example spectrum detection in a precise or fine manner, according to an embodiment of the invention. In particular, in FIG. 3 , three sharp peaks are shown for each signal, indicating a better detection performance in terms of sensing resolution.
  • the sparse or coarse MRSS procedure illustrated by FIG. 3B may take a shorter sensing time compared to the precise or fine MRSS procedure illustrated by FIG. 3C . Therefore, the overall MRSS procedure in accordance with an embodiment of the invention may be operative to examine a wideband spectrum in a fast and sparse manner and, if needed, in a precise manner without any increase of hardware burden.
  • FIG. 4 illustrates an example flow diagram of a spectrum-sensing and decision procedure, according to an embodiment of the invention.
  • the coarse scanning procedure may be initialized (block 402 ).
  • the coarse scanning stage may estimate the channel power for a wideband spectrum and classifies each unit channel into one of three candidate channels—a vacant channel, a strong signal channel, or a weak signal channel (block 404 ).
  • the fine scanning procedure may then be initialized (block 406 ), and the resulting candidate channels may be scanned in a precise manner in a fine scanning procedure (block 408 ).
  • double testing e.g., channel power testing and peak-count testing
  • the decision stage may announce the final result of spectrum usage status “vacant” or “occupied” for each channel (block 410 ).
  • a coarse scanning procedure in accordance with an example embodiment of the invention may examine input RF spectrum over wide span with coarse resolution MRSS.
  • the resulting coarse MRSS result for each channel may be compared with the dual thresholds to classify the corresponding channel index to three categories—vacant candidate channel and strong, weak signal-reception candidate channels.
  • FIG. 5 illustrates a flow diagram of a course scanning procedure, according to an example embodiment of the invention.
  • the MRSS procedure may be initialized (block 502 ), according to an example embodiment of the invention.
  • Input RF spectrum over a wide span may then be scanned with coarse resolution MRSS parameters (provided by block 506 ) to provide power estimation values, P CH,k , for each unit channel K (block 504 ).
  • coarse MRSS parameters may include the wavelet bandwidth Bw_c, the frequency sweep increment Fsw_c, the bandwidth Bt of the target primary signal, the start frequency Fstart, the stop frequency Fstop, and the number of averages Navg that determines the number of iterations for the coarse MRSS scan.
  • the wavelet bandwidth Bw_c and the frequency sweep increment Fsw_c may be related to the bandwidth, Bt, of the target primary signal according to eq. (1) and (2) below.
  • Bw — c ( Bt/ 2) eq. (1)
  • Fsw_c Bt eq. (2)
  • the coarse MRSS scan of block 504 may be repeated N_avg times, and the resulting power estimation values P CH,k of block 504 may be averaged for each channel K (block 508 ). Accordingly, the coarse MRSS scan of block 504 may be repeated N_avg times, with the iteration counter Itr incremented each time (block 512 ), until the iteration counter Itr reaches the limit of Navg (block 510 ).
  • the averaged power estimation value P CH,k for the k-th channel may converge to a certain value that may be substantially immune to the input noise effect.
  • the averaging process may increase the sensing time consumed for the coarse spectrum-sensing procedure.
  • the number of averages, N_avg may be selected to provide noise immunity as well as to minimize or otherwise achieve the desired coarse spectrum-sensing time.
  • the averaged power estimation values P CH,k may optionally be converted to decibels (dB), according to an example embodiment of the invention (block 512 ).
  • the averaged power estimation values P CH,k may then be subject to at least dual threshold testing to classify the channels K as occupied (e.g., weak, strong) or vacant candidate channels, as will be described with respect to blocks 514 and 520 below.
  • dual threshold testing in accordance with an embodiment of the invention may be utilized since the primary spectrum user signals may have wide range of power levels. Indeed, a single threshold value, applied to the wide range of signal level powers may be insufficient due to misdetection events and false alarm rates. For example, if the single threshold value were set too high, there will be too few channels K that will not be detected being occupied. On the other hand, if the single threshold value were set too low, there will be too many channels K that will be detected as being occupied.
  • dual-mode threshold levels may be applied to the averaged channel power values P CH,k , as illustrated in blocks 514 and 520 .
  • a dual mode threshold test a strong threshold TH_S test for strong mode (block 514 ) and a weak threshold TH_W test for weak mode (block 520 )—each channel K may be classified as a “vacant” or occupied (e.g., strong, weak) candidate channel.
  • the channel K will be classified as a “vacant” candidate channel with noise-level power reception and added to the vacant candidate channel index (block 524 ). If the channel power value P CH,k for a particular channel K satisfies the strong threshold TH_S test (block 514 ), then the channel K will be classified as an occupied candidate channel with “strong” signal reception and added to the strong candidate channel index (block 518 ).
  • FIG. 6 illustrates the strong threshold TH_S and the weak threshold TH_S as applied to a example plurality of channels K, according to an example embodiment of the invention.
  • TH — S N _global — db +( D/U ) — dB+CNRdb _min eq. (3)
  • TH — W N _global — db+CNRdb _min eq. (4)
  • the (D/U)_dB may be the ratio of the desired and undesired signal power levels of the primary signal reception events.
  • the CNRdb_min in eq. (3) and eq. (4) may be the carrier-to-noise ratio for the signal reception of the sensitivity case of the spectrum sensing technique.
  • the global noise reference level N_global_db in eq. (3) and eq. (4) may be the minimum of the coarse MRSS scanned P CH,k values, according to an example embodiment of the invention.
  • the global noise reference level N_global_db may be selected from the noise-level estimation values scanned over very wideband spectrum enough to encounter at least a vacant channel. Moreover, this N_global_db may also be used as the reference of the channel power testing in the following fine scanning procedure.
  • the channel index lists classified to three categories Iv, Is, and Iw corresponding to “vacant,” “strong,” and “weak” channels K, respectively, may be transferred to the fine scanning and testing procedure for the final decision of each channel K usage status (block 526 ).
  • the candidate channel index lists Iv, Is, and Iw generated in blocks 524 , 518 , and 522 of FIG. 5 may be investigated precisely in a fine scanning procedure through the examination methods and criteria corresponding to each channel category.
  • FIG. 7 shows a flow diagram of the fine scanning procedure, according to an embodiment of the invention.
  • each of the strong, weak, or vacant candidate channel indexes Iv, Is, Iw may be provided for respective vacant-bin candidate testing (block 704 ), strong-bin candidate testing (block 702 ), and weak-bin candidate testing (block 706 ), according to an example embodiment of the invention.
  • the channel K may be declared as a vacant channel (block 720 ).
  • the channel K may be additionally subject to weak-bin candidate testing (block 706 ).
  • a channel K on the strong candidate channel index Is is confirmed to be a strong channel (block 708 )
  • the channel K may be declared as a strong channel (block 710 ) and/or occupied (block 712 ).
  • the channel K may additionally be subject to weak-bin candidate (block 706 ).
  • a channel K either from the weak candidate channel index Iw or blocks 708 , 718 , is confirmed to be a weak channel (block 714 )
  • the channel K may be declared as a weak channel (block 716 ) and/or occupied (block 712 ).
  • a channel K is not confirmed to be a weak channel (block 714 )
  • it may be declared as a non-occupied channel (i.e., vacant channel) (block 720 ).
  • the vacant-bin candidate testing (block 704 ), strong-bin candidate testing (block 702 ), and weak-bin candidate testing (block 708 ) introduced in FIG. 7 will now be discussed in further detail with respect to FIGS. 8A-D and 9 .
  • each channel spectrum listed in the vacant candidate channel index Iv may be finely scanned in block 970 with fine resolution MRSS parameters provided by block 971 .
  • the fine scanning in block 970 may generate a plurality of discrete power values p K,m , where p K,m is the m-th discrete power value scanned for the K-th channel with fine scanning conditions.
  • FIG. 10 illustrates examples of discrete power values p K,m that are obtained by scanning with fine scanning conditions.
  • the fine MRSS parameters provided by block 971 may include the wavelet sweep frequency Fw_f the frequency sweep increment Fsw_f, and the bandwidth Bt of the target primary signal.
  • the wavelet bandwidth Bw_f and the frequency sweep increment Fsw_f may be related to the bandwidth Bt of the target primary signal according to eq. (5) and (6) below.
  • Bw — f ( 1/20) ⁇ Bt ⁇ ( 1/10) ⁇ Bt eq. (5)
  • Fsw_f Bw_f eq. (6)
  • the average channel power P CH,K may be calculated by averaging the discrete power values p K,m for each channel K according to eq. (7), where M is the total number of fine scanned peaks per channel (block 954 ).
  • This average channel power P CH,K for each channel K in the vacant candidate channel index Iv may be optionally be converted to decibals (dB) (block 974 ), according to an example embodiment of the invention.
  • the average channel power P CH,K for each channel K may be compared with a threshold Pthrs, which may be the global noise reference N_global_db (provided by block 977 ) from the coarse scanning stage. If the average channel power P CH,K is smaller than the global noise reference N_global_db, then the corresponding channel may be transferred to the final decision stage and recorded as the vacant channel (block 986 ). Otherwise, the channel index may be added to the weak channel index, Iw, for the further investigation for the weak signal reception, as described in further detail with respect to block 950 and subsequent blocks.
  • each channel spectrum listed in the strong candidate channel index Is may be scanned (block 902 ) with fine resolution MRSS parameters provided by block 904 , as described with respect to in eq. (5) and (6) above.
  • the average channel power P CH,K may be calculated by averaging the discrete power values p K,m for each channel K according to eq. (7) (block 906 ).
  • This average channel power P CH,K for each channel in the strong candidate channel index “Is” may be optionally be converted to decibals (dB) (block 908 ), according to an example embodiment of the invention.
  • the average channel power P CH,K , for each channel in the strong candidate index Is may then be compared with a threshold Pthrs such as a strong mode threshold, TH_S, from the coarse scanning stage (block 910 ). If the average channel power P CH,K is larger than the strong mode threshold TH_S (block 910 ), the corresponding channel is transferred to the peak-count testing (block 914 ) for the further investigation for the strong signal reception. Otherwise, the channel index may be added to the weak channel index Iw for the further investigation for the weak signal reception (block 950 ).
  • the discrete power values p K,m for each channel K listed in the strong candidate index Is may be compared to a given threshold value Pthrs obtained at least in part from block 912 .
  • this threshold value Pthrs may be an average or median value PM K , of the maximum and the minimum of the discrete power values p K,m for each channel K, as illustratively shown in FIG. 9 .
  • the number of peaks having the power value greater than this threshold value Pthrs may then be counted in blocks 916 , 918 .
  • a discrete power value p K,m is greater than the threshold value Pthrs in block 914 , then the peak count may be incremented (block 918 ). Otherwise, the peak count remains the same and is not incremented (block 916 ).
  • This peak count process described in blocks 914 - 918 may then be repeated with an interactive counter i being incremented (block 921 ) until the total number B_s of discrete power values p K,m for each channel K have been examined (block 920 ). The resulting final peak-count for each channel K may then be compared with a given peak-count threshold value, N peak — S in block 922 .
  • this channel passes the peak-count testing as well. In this situation, the corresponding channel index may be transferred to the final decision stage and recorded as the strong signal reception channel (block 982 ). On the other hand, if this channel K does not pass the peak-count testing (block 922 ), this channel index is added to the weak channel index, Iw, for the further investigation for the weak signal reception (block 950 ). According to an example embodiment of the invention, this strong channel testing may prevent the potential false-alarm for the alias due to the adjacent strong signal spectrum.
  • the weak candidate channel index list Iw may include three parts: the channel index numbers (i) categorized as the weak candidate channel in the coarse scanning stage, (ii) transferred from the vacant channel testing by failing the channel power test (block 976 ), and (iii) transferred from the strong channel testing by failing the channel power test or the peak-count testing (block 922 ).
  • each channel spectrum, listed in the candidate channel index Iw is scanned with fine resolution MRSS parameters provided by block 953 , as similarly described with respect to eq. (5) and (6) (block 952 ).
  • the average channel power, P CH,K is calculated by averaging the discrete power values p K,m for each channel according to eq. (7).
  • This average channel power P CH,K , for each channel K in the weak candidate channel index Iw may be optionally converted to decibals (dB) (block 956 ), according to an example embodiment of the invention.
  • the average channel power P CH,K for each channel K may be compared with a threshold Pthrs, which may be a weak mode threshold, TH_W (provided by block 960 ), from the coarse scanning stage.
  • this weak channel testing may prevent the potential false-alarm due to the alias from the adjacent strong signal spectrum or due to the channel power estimation from the coarse resolution scanning.
  • the discrete power values p K,m values for each channel K listed in the weak candidate index Iw may be compared to a given threshold value Pthrs obtained at least in part from block 960 .
  • this threshold value Pthrs may be an average or median value PM K of the maximum and the minimum of the discrete power values p K,m for each channel K, as illustratively shown in FIG. 9 .
  • the number of peaks having the power value greater than this threshold value Pthrs may then be counted in blocks 962 , 964 .
  • a discrete power value p K,m is greater than the threshold value Pthrs in block 960 , then the peak count may be incremented (block 964 ). Otherwise, the peak count remains the same and is not incremented (block 962 ).
  • This peak count process described in blocks 960 - 964 may then be repeated with an interactive counter i being incremented (block 967 ) until the total number B_w of discrete power values p K,m for each channel K have been examined (block 966 ). The resulting final peak-count for each channel K may then be compared with a given peak-count threshold value, N peak — w.
  • this channel passes the peak-count testing as well. In this situation, the corresponding channel index is transferred to the final decision stage and recorded as the weak signal reception channel (block 984 ). On the other hand, if this channel K does not pass the peak-count testing (block 968 ), this channel index is transferred to the final decision stage and recorded as the vacant channel (block 986 ).
  • the averaging process is applied to the fine scanning stages in block 902 , 952 , 970 .
  • the fine MRSS scanning in blocks 902 , 952 , 970 may be repeated by N_s, N_w, or N_v times, for strong, weak and vacant channel cases, respectively.
  • the signal spectrum in the strong candidate channel list may have relatively larger signal-to-noise (SNR) ratio compared to the signal spectrum in the vacant or weak candidate channel list.
  • SNR signal-to-noise
  • a smaller value of N_s may be enough compared to the N_w or N_v.
  • the channel lists passed the strong- and weak-channel testing may be merged to provide the final list of the occupied channels (e.g., actually occupied channels) (block 988 ).
  • the occupied channel list (block 988 ) may then be reported to medium access control (MAC) unit (block 990 ) to avoid the interference to the primary spectrum users as well as the CR users.
  • MAC medium access control
  • the vacant channel lists from the vacant- and weak-channel testing results may be merged to provide the final list of the vacant channels (e.g., actually vacant channels) (block 986 ).
  • the corresponding channel list (block 986 ) may be reported to medium access control unit to assign these channels for use as a potential CR link.
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DE102007046595A DE102007046595A1 (de) 2006-09-29 2007-09-27 Algorithmen und Verfahren zum Abfühlen eines Spektrums #
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CN2007101514248A CN101155423B (zh) 2006-09-29 2007-09-28 频谱感知算法和方法
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